STAT545-hw-Dong-Xinzhe

Homeworks:

Contents of homeworks:

hw01 :

• Create a New Repo, and edit README.md as a self introduction
• Add R Markdown and Markdown for Gapminder exploration

hw02 :

• Explore the data, get to know the variables
• Explore various plot types with ggplot2
• Use filter(), select() and %>%

hw03 :

• Manipulate and explore a dataset with the dplyr package
• Visualizations made with ggplot2

hw04 :

• Reshape a data frame using gather() and spread() function from tidyr
• Practice join() functions

hw05 :

• Reorder a factor using the forcats package, and explore its effects on figures
• Improve a figure made previously, implement visualization design principles
• Write some data to file and load it back into R using write_csv()/read_csv(), and saveRDS()/readRDS()
• Writing figures to file using ggsave()

hw06 :

• Writing functions. Write two functions that do linear regression and robust regression on the Gapminder data, and compare their estimated mean square prediction error (mspe).
• Work with a nested data frame. Create a nested data frame using the function nest() and map a function over the list column holding the nested data. Get information out of the linear models using the tidy() functions. Use the usual dplyr, tidyr, and ggplot2 workflows to make explorations.
• Working on some of the exercises from the Strings chapter.

hw07 :

• Write three Rscripts and one Rmarkdown to carry out a small data analysis.
• Build an automated data analysis pipeline.
• Automate the pipeline using two methods: the master R script Makefile.R and Makefile.

hw08 :

• Add more features to the BC Liquor Store app we created in class.
• Publish the app on shinyapps.io.

hw09 :

• Develop the powers() package.
• Define and export two new functions: box_cox() and my_log().
• Document all exported functions and push the package to GitHub.

hw10 :

• Get data from the internet into R using two methods:
• Make API queries “by hand” using httr.
• Scrape the web.

Useful links:

• The Link to the main STAT545 webpage.

• A detailed tutorial about Rmarkdown.

• A cheatsheet of Markdown.

• A ggplot tutorial.

• A tutorial about making a table with pander package.

• Jenny's notes and example about the gather() function.

• The tutorial about the forcats package.